Transcriptome of microbiome for the nematode Caenorhabditis elegans
Ontology highlight
ABSTRACT:
ORGANISM(S): Caenorhabditis elegans
PROVIDER: GSE111364 | GEO | 2019/02/25
REPOSITORIES: GEO
Similar Datasets
Project description:Only recently, the natural gut microbiome of the model organism Caenorhabditis elegans has been described. C. elegans harbors a distinct gut microbiome that is shaped by environmental conditions, age, and host genotype. However, there is not much known about the genetic factors on the molecular level that the worm employs in order to keep its microbiota at bay. Previously, we have shown that TGFβ/BMP immune signaling is able to control the gut microbiome of C. elegans in particular in regards to Enterobacter species. We now aimed to identify the downstream targets of TGFβ/BMP immune signaling that implement the changes in microbiome composition. Hence, we exposed TGFβ mutants, dbl-1(nk3) and sma-3(e491), overexpression strain ctIs40 [dbl-1(+) + sur-5::GFP], and wild-type N2 to a synthetic microbiota community, CeMbio, and an E. coli OP50 control, and performed RNAseq. CeMbio is a collection of 12 diverse bacterial strains, previously isolated from wild C. elegans, C. elegans grown in microcosms, or substrates with C. elegans. Using the R packages edgeR and limma we are currently analyzing the data to understand the involvement of TGFβ/BMP signaling in host-microbiome interaction.
2023-10-31 | GSE186653 | GEO
Project description:We sequenced the transcriptome of a host (Caenorhabditis elegans) following its interaction with a non-native bacterium (Enterococcus faecalis) that has protective traits against the pathogen, Staphylococcus aureus. We also investigated the impact that the evolutionary history of the protective bacterium has on the transcriptional history of the host. We tested protective bacteria that had either coevolved against the pathogen within C. elegans, or had evolved on its own within C. elegans.
2021-04-20 | GSE151731 | GEO
Project description:microRNAs (miRNAs) are small non-coding RNA-molecules that influence translation by binding to the target gene mRNA. Many miRNAs are found in nested arrangements within introns, or exons, of larger protein-coding host genes. miRNAs and host genes in a nested arrangement are often transcribed simultaneously, which may indicate that both have similar functions. miRNAs have been implicated in regulating defense responses against pathogen infection in C. elegans and in mammals. Here, we asked if miRNAs in nested arrangements and their host genes are involved in the C. elegans response against infection with Bacillus thuringiensis (Bt). We performed miRNA sequencing and functional genetic analysis of miRNA and/or host gene in four nested arrangements. We identified mir-58.1 and mir-2 as negative regulators of C. elegans resistance to Bt infection. However, we did not find any miRNA/host gene pair in which both contribute to defense against Bt.
2021-05-17 | GSE174514 | GEO
Project description:Yilmaz2016 - Genome scale metabolic model -
Caenorhabditis elegans (iCEL1273)
This model is described in the article:
A Caenorhabditis elegans
Genome-Scale Metabolic Network Model.
Yilmaz LS, Walhout AJ.
Cell Syst 2016 May; 2(5): 297-311
Abstract:
Caenorhabditis elegans is a powerful model to study
metabolism and how it relates to nutrition, gene expression,
and life history traits. However, while numerous experimental
techniques that enable perturbation of its diet and gene
function are available, a high-quality metabolic network model
has been lacking. Here, we reconstruct an initial version of
the C. elegans metabolic network. This network model
contains 1,273 genes, 623 enzymes, and 1,985 metabolic
reactions and is referred to as iCEL1273. Using flux balance
analysis, we show that iCEL1273 is capable of representing the
conversion of bacterial biomass into C. elegans biomass
during growth and enables the predictions of gene essentiality
and other phenotypes. In addition, we demonstrate that gene
expression data can be integrated with the model by comparing
metabolic rewiring in dauer animals versus growing larvae.
iCEL1273 is available at a dedicated website
(wormflux.umassmed.edu) and will enable the unraveling of the
mechanisms by which different macro- and micronutrients
contribute to the animal's physiology.
This model is hosted on
BioModels Database
and identified by:
MODEL1604210000.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2016-11-03 | MODEL1604210000 | BioModels
Project description:On going efforts are directed at understanding the mutualism between the gut microbiota and the host in breast-fed versus formula-fed infants. Due to the lack of tissue biopsies, no investigators have performed a global transcriptional (gene expression) analysis of the developing human intestine in healthy infants. As a result, the crosstalk between the microbiome and the host transcriptome in the developing mucosal-commensal environment has not been determined. In this study, we examined the host intestinal mRNA gene expression and microbial DNA profiles in full term 3 month-old infants exclusively formula fed (FF) (n=6) or breast fed (BF) (n=6) from birth to 3 months. Host mRNA microarray measurements were performed using isolated intact sloughed epithelial cells in stool samples collected at 3 months. Microbial composition from the same stool samples was assessed by metagenomic pyrosequencing. Both the host mRNA expression and bacterial microbiome phylogenetic profiles provided strong feature sets that clearly classified the two groups of babies (FF and BF). To determine the relationship between host epithelial cell gene expression and the bacterial colony profiles, the host transcriptome and functionally profiled microbiome data were analyzed in a multivariate manner. From a functional perspective, analysis of the gut microbiota's metagenome revealed that characteristics associated with virulence differed between the FF and BF babies. Using canonical correlation analysis, evidence of multivariate structure relating eleven host immunity / mucosal defense-related genes and microbiome virulence characteristics was observed. These results, for the first time, provide insight into the integrated responses of the host and microbiome to dietary substrates in the early neonatal period. Our data suggest that systems biology and computational modeling approaches that integrate “-omic” information from the host and the microbiome can identify important mechanistic pathways of intestinal development affecting the gut microbiome in the first few months of life. KEYWORDS: infant, breast-feeding, infant formula, exfoliated cells, transcriptome, metagenome, multivariate analysis, canonical correlation analysis 12 samples, 2 groups
2012-03-19 | E-GEOD-31075 | biostudies-arrayexpress
Project description:Microbiomes of life-history stages of Hydroides elegans
| PRJNA418344 | ENA
Project description:The early-life intestinal microbiota plays a key role in shaping host immune system development. We found that a single early-life antibiotic course (1PAT) accelerated Type 1 diabetes (T1D) development in male NOD mice. The single course had strong and persistent effects on the intestinal microbiome, selecting for a highly metabolically active metagenome, with altered hepatic and serum metabolites. The exposure led to differential ileal and hepatic histone modification, and perturbed ileal gene expression, strongly affecting the normal maturational pattern. Earliest effects involved specific genes in innate immune pathways, with later effects on adaptive immunity. Microbiome analysis revealed four potential T1D-protective taxa and four T1D-accelerating taxa, and a network linking specific microbial taxa to differences in ileal gene expression was identified. This simplified animal model has improved understanding of the mechanisms by which early-life gut microbiome perturbations alter host intestinal responses, contributing to T1D.
2018-08-03 | GSE101721 | GEO
Project description:Human activity is altering the environment at a rapid pace, challenging the adaptive capacities of genetic variation within animal populations. Animals also harbor extensive gut microbiomes, which play diverse roles in host health and fitness and may help expanding host capabilities. The unprecedented scale of human usage of xenobiotics and contamination with environmental toxins describes one challenge against which bacteria with their immense biochemical diversity are particularly suited to offer solutions. To explore the paths leading to bacteria-assisted rapid adaptation, we used Caenorhabditis elegans harboring a defined microbiome, and the antibiotic neomycin as a model toxin, harmful for the worm host and neutralized to different extents by microbiome members. Worms exposed to neomycin showed delayed development and decreased survival but were protected when colonized by neomycin-resistant members of the microbiome. Through a combination of 16S gene sequencing, counting of live bacteria and behavioral assays we identified two distinct mechanisms that facilitated adaptation: gut enrichment for a neomycin-modifying strain driven by altered bacterial competition; and host avoidance behavior, which depended on the stress-activated KGB-1/JNK and enabled preference of neomycin-protective bacteria. The straightforwardness of these mechanisms suggests that bacteria-assisted host adaptation may be more common than currently appreciated, protecting animals from novel stressors. However, gut remodeling may also cause dysbiosis, and additional experiments identified fitness trade-offs including increased susceptibility to infection as well as metabolic remodeling. Extending these results to other toxins suggests yet unaccounted-for microbiome-dependent long-term consequences of toxin exposure.
2023-11-09 | GSE246966 | GEO
Project description:Restif2006 - Whooping cough
This model is described in the article:
Integrating life history and
cross-immunity into the evolutionary dynamics of pathogens.
Restif O, Grenfell BT.
Proc. Biol. Sci. 2006 Feb; 273(1585):
409-416
Abstract:
Models for the diversity and evolution of pathogens have
branched into two main directions: the adaptive dynamics of
quantitative life-history traits (notably virulence) and the
maintenance and invasion of multiple, antigenically diverse
strains that interact with the host's immune memory. In a first
attempt to reconcile these two approaches, we developed a
simple modelling framework where two strains of pathogens,
defined by a pair of life-history traits (infectious period and
infectivity), interfere through a given level of
cross-immunity. We used whooping cough as a potential example,
but the framework proposed here could be applied to other acute
infectious diseases. Specifically, we analysed the effects of
these parameters on the invasion dynamics of one strain into a
population, where the second strain is endemic. Whereas the
deterministic version of the model converges towards stable
coexistence of the two strains in most cases, stochastic
simulations showed that transient epidemic dynamics can cause
the extinction of either strain. Thus ecological dynamics,
modulated by the immune parameters, eventually determine the
adaptive value of different pathogen genotypes. We advocate an
integrative view of pathogen dynamics at the crossroads of
immunology, epidemiology and evolution, as a way towards
efficient control of infectious diseases.
This
version of the model can be used for both the stochastic and the
deterministic simulations described in the article. For
deterministic interpretations with infinite population sizes, set
the population size
N = 1. The model reproduces the deterministic time
courses. Stochastic interpretation with Copasi UI gave results
similar to the article, but was not extensively tested. The
initial conditions for competition simulations can be derived by
equilibrating the system for one pathogen and then adding a
starting concentration for the other.
Originally
created by libAntimony v1.3 (using libSBML 4.1.0-b1)
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000249.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2024-09-02 | BIOMD0000000249 | BioModels